This paper provides a fundamental research review of Reconfigurable Manufacturing
Systems (RMS), which uniquely explores the state-of-the-art in distributed and decentralized …

In the last few years, the application of Machine Learning approaches like Deep Neural
Network (DNN) models have become more attractive in the healthcare system given the …

Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …

The security and privacy concerns along with the amount of data that is required to be
processed on regular basis has pushed processing to the edge of the computing systems …

Artificial intelligence (AI) has successfully made its way into contemporary industrial sectors
such as automobiles, defense, industrial automation 4.0, healthcare technologies …

Low-cost, high-performance embedded devices are proliferating and a plethora of new
platforms are available on the market. Some of them either have embedded GPUs or the …

With the advent of artificial intelligence (AI), there has been an attempt to model a similar
behavior among computers, so that they can make decisions autonomously, just like …

Convolutional Neural Networks (CNN) have shown impressive performance in computer
vision, natural language processing, and many other applications, but they exhibit high …

The ubiquitous use of IoT and machine learning applications is creating large amounts of
data that require accurate and real-time processing. Although edge-based smart data …

An exploding demand for processing capabilities related to the emergence of the Internet of
Things (IoT), Artificial Intelligence (AI), and big data, has led to the quest for increasingly …